In this piece I’ll just focus on one aspect of technology – artificial intelligence or AI – that is likely to shape many aspects of the retail business and the consumer’s experience over the coming years.
To be able to see the scope of its potential all-pervasive impact we need to go beyond our expectations of humanoid robots. We also need to understand that artificial intelligence works on a cycle of several mutually supportive elements that enable learning and adaptation. The terms “big data” and “analytics” have been bandied about a lot, but have had limited impact so far in the retail business because it usually only touches the first two, at most three, of the necessary elements.
“Big data” models still depend on individuals in the business taking decisions and acting based on what is recommended or suggested by the analytics outputs, and these tend to be weak links which break the learning-adaptation chain. Of course, each of these elements can also have AI built in, for refinement over time.
Certainly retailers with a digital (web or mobile) presence are in a better position to use and benefit from AI, but that is no excuse for others to “roll over and die”. I’ll list just a few aspects of the business already being impacted and others that are likely to be in the future.
Know the customer: The most obvious building block is the collection of customer data and teasing out patterns from it. This has been around so long that it is surprising what a small fraction of retailers have an effective customer database. While we live in a world that is increasingly drowning in information, most retailers continue to collect and look at very few data points, and are essentially institutionally “blind” about the customers they are serving.
However, with digital transactions increasing, and compute and analytical capability steadily become less expensive and more flexible via the cloud, information streams from not only the retailers’ own transactions but multiple sources can be tied together to achieve an ever-better view of the customer’s behaviour.
Prediction and Response: Not only do we expect “intelligence” to identify, categorise and analyse information streaming in from the world better, but to be able to anticipate what might happen and also to respond appropriately.
Predictive analytics have been around in the retail world for more than a decade, but are still used by remarkably few retailers. At the most basic level, this can take the form of unidirectional reminders and prompts which help to drive sales. Remember the anecdote of Target (USA) sending maternity promotions based on analytics to a young lady whose family was unaware of her pregnancy?
However, even automated service bots are becoming more common online, that can interact with customers who have queries or problems to address, and will get steadily more sophisticated with time. We are already having conversations with Siri, Google, Alexa and Cortana – why not with the retail store?
Visual and descriptive recognition: We can describe to another human being a shirt or dress that we want or call for something to match an existing garment. Now imagine doing the same with a virtual sales assistant which, powered by image recognition and deep learning, brings forward the appropriate suggestions. Wouldn’t that reduce shopping time and the frustration that goes with the fruitless trawling through hundreds of items?
Augmented and virtual reality: Retailers and brands are already taking tiny steps in this area which I described in another piece a year ago (“Retail Integrated”) so I won’t repeat myself. Augmented reality, supported by AI, can help retail retain its power as an immersive and experiential activity, rather than becoming purely transaction-driven.
On the consumer-side, AI can deliver a far higher degree of personalisation of the experience than has been feasible in the last few decades. While I’ve described different aspects, now see them as layers one built on the other, and imagine the shopping experience you might have as a consumer. If the scenario seems as if it might be from a sci-fi movie, just give it a few years. After all, moving staircases and remote viewing were also fantasy once.
On the business end it potentially offers both flexibility and efficiency, rather than one at the cost of the other. But we’ll have to tackle that area in a separate piece.
Third Eyesight’s CEO, Devangshu Dutta recently participated in a discussion about the phenomenal growth of the Patanjali brand, from yoga lessons to a food and FMCG conglomerate taking well-established multinational and Indian competitors head-on. In a conversation with Zee Business anchor, P. Karunya Rao and FCB-Ulka’s chairman Rohit Ohri, Devangshu shared his thoughts on the factors playing to Patanjali’s advantage. Excerpts from the conversation were telecast on Brandstand on Zee Business:
In about 20 years, Café Coffee Day (CCD) has grown from one ‘cyber café’ in Bengaluru to the leading chain of cafés in the country by far.
In its early years, it was a conservative, almost sleepy, business. The launch of Barista in the late 1990s and its rapid growth was the wake-up call for CCD — and wake up it did!
CCD then expanded aggressively. It focussed on the young and more affluent customers. Affordability was a keystone in its strategy and it largely remains the most competitively priced among the national chains.
Its outlets ranged widely in size — and while this caused inconsistency in the brand’s image — it left competitors far behind in terms of market coverage. However, the market hasn’t stayed the same over the years and CCD now has tough competition.
CCD competes today with not only domestic cafés such as Barista or imports such as Costa and Starbucks, but also quick-service restaurants (QSRs) such as McDonald’s and Dunkin’ Donuts. In the last couple of years, in large cities, even the positioning of being a ‘hang-out place’ is threatened by a competitor as unlikely as the alcoholic beverage-focussed chain Beer Café.
CCD is certainly way ahead of other cafés in outlet numbers and visibility in over 200 cities. It has an advantage over QSRs with the focus on beverage and meetings, rather than meals. Food in CCD is mostly pre-prepared rather than in-store (unlike McD’s and Dunkin’) resulting in lower capex and training costs, as well as greater control since it’s not depending on store staff to prepare everything. However, rapid expansion stretches product and service delivery and high attrition of front-end staff is a major operational stress point. Upmarket initiatives Lounge and Square, which could improve its average billing, are still a small part of its business.
Delivery (begun in December 2015) and app-orders seem logical to capture busy consumers, and to sweat the assets invested in outlets. However, for now, I’m questioning the incremental value both for the consumer and the company’s ROI once all costs (including management time and effort) are accounted for. The delivery partner is another variable (and risk) in the customer’s experience of the brand. Increasing the density through kiosks and improving the quality of beverage dispensed could possibly do more for the brand across the board.
The biggest advantage for CCD is that India is a nascent market for cafés. The café culture has not even scratched the surface in the smaller markets and in travel-related locations. The challenge for CCD is to act as an aggressive leader in newer locations, while becoming more sophisticated in its positioning in large cities. It certainly needs to allocate capex on both fronts but larger cities need more frequent refreshment of the menu and retraining of staff.
An anonymous Turkish poet wrote: “Not the coffee, nor the coffeehouse is the longing of the soul. A friend is what the soul longs for, coffee is just the excuse.” There are still many millions of friends in India for whom the coffee-house remains unexplored territory, whom CCD could bring together.
Aggregator models and hyperlocal delivery, in theory, have some significant advantages over existing business models.
Unlike an inventory-based model, aggregation is asset-light, allowing rapid building of critical mass. A start-up can tap into existing infrastructure, as a bridge between existing retailers and the consumer. By tapping into fleeting consumption opportunities, the aggregator can actually drive new demand to the retailer in the short term.
A hyperlocal delivery business can concentrate on understanding the nuances of a customer group in a small geographic area and spend its management and financial resources to develop a viable presence more intensively.
However, both business models are typically constrained for margins, especially in categories such as food and grocery. As volume builds up, it’s feasible for the aggregator to transition at least part if not the entire business to an inventory-based model for improved fulfilment and better margins. By doing so the aggregator would, therefore, transition itself to being the retailer.
Customer acquisition has become very expensive over the last couple of years, with marketplaces and online retailers having driven up advertising costs – on top of that, customer stickiness is very low, which means that the platform has to spend similar amounts of money to re-acquire a large chunk of customers for each transaction.
The aggregator model also needs intensive recruitment of supply-side relationships. A key metric for an aggregator’s success is the number of local merchants it can mobilise quickly. After the initial intensive recruitment the merchants need to be equipped to use the platform optimally and also need to be able to handle the demand generated.
Most importantly, the acquisitions on both sides – merchants and customers – need to move in step as they are mutually-reinforcing. If done well, this can provide a higher stickiness with the consumer, which is a significant success outcome.
For all the attention paid to the entry and expansion of multinational retailers and nationwide ecommerce growth, retail remains predominantly a local activity. The differences among customers based on where they live or are located currently and the immediacy of their needs continue to drive diversity of shopping habits and the unpredictability of demand. Services and information based products may be delivered remotely, but with physical products local retailers do still have a better chance of servicing the consumer.
What has been missing on the part of local vendors is the ability to use web technologies to provide access to their customers at a time and in a way that is convenient for the customers. Also, importantly, their visibility and the ability to attract customer footfall has been negatively affected by ecommerce in the last 2 years. With penetration of mobile internet across a variety of income segments, conditions are today far more conducive for highly localised and aggregation-oriented services. So a hyperlocal platform that focusses on creating better visibility for small businesses, and connecting them with customers who have a need for their products and services, is an opportunity that is begging to be addressed.
It is likely that each locality will end up having two strong players: a market leader and a follower. For a hyperlocal to fit into either role, it is critical to rapidly create viability in each location it targets, and – in order to build overall scale and continued attractiveness for investors – quickly move on to replicate the model in another location, and then another. They can become potential acquisition targets for larger ecommerce companies, which could acquire to not only take out potential competition but also to imbibe the learnings and capabilities needed to deal with demand microcosms.
High stake bets are being placed on this table – and some being lost with business closures – but the game is far from being played out yet.
The Patanjali Group has created an Indian FMCG giant in a very short span of time on the back of a three-pronged strategy:
The enormous brand awareness that can be attributed to the very high visibility of Baba Ramdev, across a variety of media and issues,
Wide and deep market penetration through a large network of outlets and distributors across the country, and
Pricing itself below the benchmark competitor in each product area in which it is competing.
Over time, the group has also invested in improving its manufacturing and packaging infrastructure to bring itself on par with well-established competitors.
The group has clearly focussed itself on the mass market, and Patanjali Group’s products become a “go-to” for customers who are more price-sensitive than brand-loyal. This definitely creates pressure on established brands in each of the product segments where the group is now present.
In the growing market for ready-to-cook packaged food, a new entrant would struggle to create visibility and initial demand. However, with the momentum of the Patanjali brand behind it, the group’s new product — instant noodles — has a fighting chance.
I must say, though, that the immediate opportunity would have been bigger had Maggi also not just relaunched in the market. The other aspect to keep in mind is that while a lot of food and nutraceutical products resonate easily with the Patanjali brand, instant noodles seem completely counter-intuitive under this brand’s umbrella. How much consumers will support this new launch remains to be seen.
This 2-4 minute noodles story is still cooking. Keep watching the pot!